This project involves the development and application of microcomputer-based signal processing techniques for analysis of physiological signals e.g., electrocardiogram, electromyogram, and electroencephalogram. The LAS microcomputer-based systems provide a general purpose analog-to-digital conversion facility and an ability to filter the signals with a variety of analog and digital techniques (before and/or after A/D conversion). An important component of this project is the modeling of the physiological system that produces the signals. To serve this purpose LAS has acquired and is testing several software packages including SIMULINK, NEURALNET TOOLBOX, and SYSTEM IDENTIFICATION SOFTWARE (supplied by Mathworks) and HISPEC (supplied by United Signals and Systems, Inc.), which uses autoregressive modeling to produce an autocorrelation function and Fourier transform to produce very high resolution power spectra. These packages are being integrated into MATLAB. If these software packages prove themselves in tests with real and/or simulated physiological signal data, they will be implemented on Macintosh platforms. A main objective of this project includes methodology for guaranteeing the fidelity of physiological signals which can be critically important to diagnostic interpretation (e.g. in electrocardiology). A further objective is to use advanced mathematical and modeling techniques to separate pathophysiology from normal.